Balcilar, MehmetAkadiri, Seyi SaintGupta, RanganMiller, Stephen M.2019-03-052019-02Balcilar, M., Akadiri, S.S., Gupta, R. et al. Partisan Conflict and Income Inequality in the United States: A Nonparametric Causality-in-Quantiles Approach. Social Indicators Research (2019) 142: 65-82. https://doi.org/10.1007/s11205-018-1906-3.0303-8300 (print)1573-0921 (online)10.1007/s11205-018-1906-3http://hdl.handle.net/2263/68568This paper examines the predictive power of a partisan conflict on income inequality. Our study contributes to the existing literature by using the newly introduced nonparametric causality-in-quantile testing approach to examine how political polarization in the United States affects several measures of income inequality and distribution overtime. The study uses annual time-series data between the periods 1917–2013. We find evidence in support of a dynamic causal relationship between partisan conflict and income inequality, except at the upper end of the quantiles. Our empirical findings suggest that a reduction in partisan conflict will lead to a reduction in our measures of income inequality, but this requires that inequality is not exceptionally high.en© Springer Science+Business Media B.V., part of Springer Nature 2018. The original publication is available at http://link.springer.com/journal/11205.Income inequalityPartisan conflictQuantile causalityPartisan conflict and income inequality in the United States : a nonparametric causality-in-quantiles approachPostprint Article